340 citations · 355 across the 3 of their papers we have counts for
3 papers
eess.IV2019★ 340 cited
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
Mateusz Buda, Ashirbani Saha, Maciej A Mazurowski
Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associated with shape features. In this study, we propose a fully automatic way to quant…
cs.CV2017★ 12 cited
Deep Learning for identifying radiogenomic associations in breast cancer
Zhe Zhu, Ehab Albadawy, Ashirbani Saha +3
Purpose: To determine whether deep learning models can distinguish between breast cancer molecular subtypes based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).…
cs.CV2017★ 3 cited
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ
Zhe Zhu, Michael Harowicz, Jun Zhang +4
Purpose: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the di- agnosis of ductal ca…